Code
pacman::p_load(sf, spNetwork, tmap, tidyverse, spatstat, lubridate, dplyr, reader, raster, plotly, ggplot2, spatstat)Take-home Exercise 1
1.Overview
Road traffic accidents cause approximately 1.19 million deaths and 20–50 million non-fatal injuries annually, with vulnerable road users such as pedestrians, cyclists, and motorcyclists making up more than half of these fatalities. Traffic injuries are the leading cause of death for those aged 5–29, and two-thirds of fatalities occur among working-age individuals (18–59). Low- and middle-income countries suffer 90% of global road fatalities despite having only 60% of the world’s vehicles, and road traffic accidents cost countries 3% of their GDP. Thailand has some of the deadliest roads globally, with around 20,000 deaths annually. Between 2014 and 2021, 19% of accidents occurred on national highways, with 66% of accident-prone areas located on straight road segments.
2.Get Start
2.1 Objectives
The objectives of this exercise are to discover factors influencing road traffic accidents in the Bangkok Metropolitan Region (BMR) by employing spatio-temporal point pattern analysis. Specifically, the goals are to:
1.visualize the spatio-temporal dynamics of road traffic accidents in BMR using statistical graphics and geovisualization methods.
2.conduct detailed spatial analysis using Network Spatial Point Pattern Analysis.
3.perform spatio-temporal analysis using Temporal Network Spatial Point Pattern Analysis methods.
2.2 The Study Area
The focus of this study would in Bangkok Metropolitan Region BMR.
The political definition is defined as the metropolis and the five adjacent provinces of Nakhon Pathom, Pathum Thani, Nonthaburi, Samut Prakan, and Samut Prakan.
2.3 Setting the Analytical Tools
For the purpose of this Take-home Exercise 1, these R packages will be used. They are:
sf provides functions for importing, processing, and wrangling geospatial data.
spNetwork provides methods for network-constrained spatial point pattern analysis, especially for road networks.
tmap provides functions to produce cartographic-quality thematic maps.
tidyverse, a family of R packages that provide functions for common data science tasks including data import, transformation, wrangling, and visualization.
spatstat for performing Spatial Point Pattern Analysis such as kcross, Lcross, etc.
lubridate provides functions to work with date-times and perform date-time manipulation.
dplyr provides functions for data manipulation, such as filtering, summarizing, and joining datasets.
reader provides functions for reading data into R from various formats.
raster for handling raster data in R.
sparr provides functions to estimate fixed and adaptive kernel-smoothed spatial relative risk surfaces via the density-ratio method and perform inference.
plotly provides functions for creating interactive web-based graphs.
ggplot2 provides functions for creating elegant data visualizations based on the grammar of graphics.
3 Data Preparation
3.1 Data
For the purpose of Take Home Exercise 1, three basic data sets must be used, they are:
Thailand Road Accident [2019-2022] on Kaggle
Code
acc <- read_csv("/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/thai_road_accident_2019_2022.csv") %>%
mutate(Month_num = month(incident_datetime)) %>%
mutate(Month_fac = month(incident_datetime,
label = TRUE,
abbr = TRUE)) %>%
mutate(dayofweek = weekdays(incident_datetime))%>%
filter(!is.na(longitude) & !is.na(latitude)) %>%
st_as_sf(coords = c("longitude", "latitude"),
crs=4326) %>%
st_transform(crs = 32647)Rows: 81735 Columns: 18
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (10): province_th, province_en, agency, route, vehicle_type, presumed_c...
dbl (6): acc_code, number_of_vehicles_involved, number_of_fatalities, numb...
dttm (2): incident_datetime, report_datetime
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Code
write_rds(acc, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/acc.rds")This process reads road accident data, extracts the month and day of the week from the incident date, filters out rows with missing geographic coordinates, and converts the data into a spatial format with appropriate geographical and projected coordinate reference systems, enabling further spatial analysis.
3.3.2 Import road data and administrative division data
Code
roads <- st_read(dsn = "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01",
layer = "hotosm_tha_roads_lines_shp")Reading layer `hotosm_tha_roads_lines_shp' from data source
`/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01'
using driver `ESRI Shapefile'
Simple feature collection with 2792590 features and 14 fields
Geometry type: MULTILINESTRING
Dimension: XY
Bounding box: xmin: 97.34457 ymin: 5.643645 xmax: 105.6528 ymax: 20.47168
CRS: NACode
admin_boundaries <- st_read(dsn = "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01",
layer = "tha_admbnda_adm1_rtsd_20220121")Reading layer `tha_admbnda_adm1_rtsd_20220121' from data source
`/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01'
using driver `ESRI Shapefile'
Simple feature collection with 77 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 84Code
admin_boundaries <- st_read(dsn = "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01",
layer = "tha_admbnda_adm1_rtsd_20220121")Reading layer `tha_admbnda_adm1_rtsd_20220121' from data source
`/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01'
using driver `ESRI Shapefile'
Simple feature collection with 77 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 843.3.3 Select the first-level administrative division of bmrf
Code
bmr_provinces <- c("Bangkok", "Nakhon Pathom", "Pathum Thani", "Nonthaburi", "Samut Prakan", "Samut Sakhon")
bmr_boundary <- admin_boundaries %>%
filter(ADM1_EN %in% bmr_provinces)Code
write_rds(bmr_boundary, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/bmr_boundary.rds")Code
bmr_boundary <- read_rds("/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/bmr_boundary.rds")
head(bmr_boundary)Simple feature collection with 6 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 99.8141 ymin: 13.4252 xmax: 100.9639 ymax: 14.27595
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF
1 2.417227 0.13133873 Bangkok กรุงเทพมหานคร TH10 <NA>
2 1.695100 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA>
3 1.251111 0.05323766 Nonthaburi นนทบุรี TH12 <NA>
4 1.884945 0.12698345 Pathum Thani ปทุมธานี TH13 <NA>
5 2.463030 0.17891420 Nakhon Pathom นครปฐม TH73 <NA>
6 1.566369 0.07155983 Samut Sakhon สมุทรสาคร TH74 <NA>
ADM1ALT1EN ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
1 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
2 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
3 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
4 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
5 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
6 <NA> <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo geometry
1 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.6139 13...
2 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.7306 13...
3 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.3415 14...
4 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.8916 14...
5 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.2231 14...
6 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.3091 13...This process isolates the administrative boundaries of the Bangkok Metropolitan Region (BMR) by filtering a dataset to include only the specified provinces: Bangkok, Nakhon Pathom, Pathum Thani, Nonthaburi, and Samut Prakan. This targeted selection enables a focused analysis on the geographic area within the BMR.
3.3.4 Select bmrf’s road data
Code
st_crs(roads) <- 4326Code
bmr_roads <- st_intersection(roads, bmr_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesThis process extracts the road network within the Bangkok Metropolitan Region (BMR) by conducting a spatial intersection between the road dataset and the BMR boundaries.
3.3.5 Exclude small roads in the roads
Code
bmr_roads <- bmr_roads %>%
filter(highway %in% c("motorway", "trunk", "primary", "secondary"))Code
saveRDS(bmr_roads,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_roads.rds")Code
bmr_roads <- read_rds("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_roads.rds")
head(bmr_roads)Simple feature collection with 6 features and 30 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 100.5486 ymin: 13.73046 xmax: 100.7913 ymax: 13.77135
Geodetic CRS: WGS 84
name name_en highway surface smoothness width
1 ถนนฉลองกรุง Chalong Krung Road secondary paved <NA> <NA>
5 ถนนฉลองกรุง Chalong Krung Road secondary concrete <NA> <NA>
1099 ถนนวิภาวดีรังสิต Vibhavadi Rangsit Road secondary <NA> <NA> <NA>
1101 ถนนดินแดง Din Daeng Road primary <NA> <NA> <NA>
1104 ถนนวิภาวดีรังสิต Vibhavadi Rangsit Road secondary <NA> <NA> <NA>
1106 ถนนดินแดง Din Daeng Road primary <NA> <NA> <NA>
lanes oneway bridge layer source name_th osm_id osm_type
1 <NA> yes <NA> <NA> <NA> ถนนฉลองกรุง 1125681229 ways_line
5 2 yes yes 1 Bing ถนนฉลองกรุง 116847248 ways_line
1099 <NA> yes <NA> <NA> <NA> ถนนวิภาวดีรังสิต 835519345 ways_line
1101 <NA> yes <NA> <NA> <NA> ถนนดินแดง 1055365750 ways_line
1104 <NA> yes <NA> <NA> <NA> ถนนวิภาวดีรังสิต 1306889182 ways_line
1106 <NA> yes <NA> <NA> <NA> ถนนดินแดง 1306889184 ways_line
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
1 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
5 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
1099 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
1101 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
1104 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
1106 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE date
1 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
5 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
1099 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
1101 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
1104 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
1106 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
validOn validTo geometry
1 2022-01-22 <NA> LINESTRING (100.7913 13.740...
5 2022-01-22 <NA> LINESTRING (100.7831 13.730...
1099 2022-01-22 <NA> LINESTRING (100.5514 13.769...
1101 2022-01-22 <NA> LINESTRING (100.5492 13.763...
1104 2022-01-22 <NA> LINESTRING (100.5524 13.771...
1106 2022-01-22 <NA> LINESTRING (100.5486 13.763...This process filters the road network within the Bangkok Metropolitan Region (BMR) to include only specific types of roads: motorways, trunk roads, primary roads, and secondary roads. This focuses the analysis on major roadways within the region.
3.3.6 Select the second-level administrative division of bmrf
Code
admin_city <- st_read(dsn = "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/tha_adm_rtsd_itos_20210121_shp",
layer = "tha_admbnda_adm2_rtsd_20220121")Reading layer `tha_admbnda_adm2_rtsd_20220121' from data source
`/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/tha_adm_rtsd_itos_20210121_shp'
using driver `ESRI Shapefile'
Simple feature collection with 928 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 84Code
st_crs(admin_city) <- 4326Code
selected_cities <- c("Bangkok", "Nakhon Pathom", "Pathum Thani", "Nonthaburi", "Samut Prakan", "Samut Sakhon")
bmr_city <- admin_city %>%
filter(ADM1_EN %in% selected_cities)
bmr_citySimple feature collection with 79 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 99.8141 ymin: 13.4252 xmax: 100.9639 ymax: 14.27595
Geodetic CRS: WGS 84
First 10 features:
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE
1 0.08541733 0.0004504685 Phra Nakhon พระนคร TH1001
2 0.13413177 0.0009501914 Dusit ดุสิต TH1002
3 0.67634217 0.0198588627 Nong Chok หนองจอก TH1003
4 0.08588647 0.0003369561 Bang Rak บางรัก TH1004
5 0.30172202 0.0034149298 Bang Khen บางเขน TH1005
6 0.30869124 0.0023032680 Bang Kapi บางกะปิ TH1006
7 0.11532413 0.0006716417 Pathum Wan ปทุมวัน TH1007
8 0.06166921 0.0002089751 Pom Prap Sattru Phai ป้อมปราบศัตรูพ่า TH1008
9 0.15667242 0.0011024083 Phra Khanong พระโขนง TH1009
10 0.39734629 0.0050495791 Min Buri มีนบุรี TH1010
ADM2_REF ADM2ALT1EN ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH
1 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
2 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
3 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
4 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
5 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
6 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
7 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
8 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
9 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
10 <NA> <NA> <NA> <NA> <NA> Bangkok กรุงเทพมหานคร
ADM1_PCODE ADM0_EN ADM0_TH ADM0_PCODE date validOn validTo
1 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
7 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
8 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
9 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
10 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((100.5007 13...
2 MULTIPOLYGON (((100.52 13.8...
3 MULTIPOLYGON (((100.914 13....
4 MULTIPOLYGON (((100.517 13....
5 MULTIPOLYGON (((100.61 13.8...
6 MULTIPOLYGON (((100.6291 13...
7 MULTIPOLYGON (((100.5191 13...
8 MULTIPOLYGON (((100.5157 13...
9 MULTIPOLYGON (((100.616 13....
10 MULTIPOLYGON (((100.8018 13...Code
saveRDS(bmr_city,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_city.rds")Code
bmr_city <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_city.rds")
head(bmr_city)Simple feature collection with 6 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 100.4876 ymin: 13.71808 xmax: 100.9385 ymax: 13.94649
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF ADM2ALT1EN
1 0.08541733 0.0004504685 Phra Nakhon พระนคร TH1001 <NA> <NA>
2 0.13413177 0.0009501914 Dusit ดุสิต TH1002 <NA> <NA>
3 0.67634217 0.0198588627 Nong Chok หนองจอก TH1003 <NA> <NA>
4 0.08588647 0.0003369561 Bang Rak บางรัก TH1004 <NA> <NA>
5 0.30172202 0.0034149298 Bang Khen บางเขน TH1005 <NA> <NA>
6 0.30869124 0.0023032680 Bang Kapi บางกะปิ TH1006 <NA> <NA>
ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH ADM1_PCODE ADM0_EN
1 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
2 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
3 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
4 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
5 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
6 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
ADM0_TH ADM0_PCODE date validOn validTo
1 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((100.5007 13...
2 MULTIPOLYGON (((100.52 13.8...
3 MULTIPOLYGON (((100.914 13....
4 MULTIPOLYGON (((100.517 13....
5 MULTIPOLYGON (((100.61 13.8...
6 MULTIPOLYGON (((100.6291 13...This process selects city-level administrative boundaries for the specified cities within the Bangkok Metropolitan Region (BMR) by filtering the dataset for these cities: Bangkok, Nakhon Pathom, Pathum Thani, Nonthaburi, Samut Prakan, and Samut Prakan.
3.3.7 Select the third-level administrative division of bmrf
Code
admin_3 <- st_read(dsn = "/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/tha_adm_rtsd_itos_20210121_shp",
layer = "tha_admbnda_adm3_rtsd_20220121")Reading layer `tha_admbnda_adm3_rtsd_20220121' from data source
`/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/tha_adm_rtsd_itos_20210121_shp'
using driver `ESRI Shapefile'
Simple feature collection with 7425 features and 22 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 97.34336 ymin: 5.613038 xmax: 105.637 ymax: 20.46507
Geodetic CRS: WGS 84Code
selected_cities <- c("Bangkok", "Nakhon Pathom", "Pathum Thani", "Nonthaburi", "Samut Prakan", "Samut Sakhon")
bmr_3 <- admin_3 %>%
filter(ADM1_EN %in% selected_cities)
bmr_3Simple feature collection with 477 features and 22 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 99.8141 ymin: 13.4252 xmax: 100.9639 ymax: 14.27595
Geodetic CRS: WGS 84
First 10 features:
Shape_Leng Shape_Area ADM3_EN ADM3_TH ADM3_PCODE
1 0.04769920 1.284175e-04 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101
2 0.03355050 6.068479e-05 Wang Burapha Phirom วังบูรพาภิรมย์ TH100102
3 0.01728931 1.769761e-05 Wat Ratchabophit วัดราชบพิธ TH100103
4 0.01904576 1.920433e-05 Samran Rat สำราญราษฎร์ TH100104
5 0.01523190 1.257312e-05 San Chaopho Suea ศาลเจ้าพ่อเสือ TH100105
6 0.01456981 1.292603e-05 Sao Chingcha เสาชิงช้า TH100106
7 0.03114989 4.079321e-05 Bowon Niwet บวรนิเวศ TH100107
8 0.01821968 1.566010e-05 Talat Yot ตลาดยอด TH100108
9 0.02230278 2.826988e-05 Chana Songkhram ชนะสงคราม TH100109
10 0.02904022 3.448890e-05 Ban Phan Thom บ้านพานถม TH100110
ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH ADM3ALT2TH ADM2_EN ADM2_TH
1 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
2 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
3 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
4 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
5 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
6 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
7 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
8 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
9 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
10 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
ADM2_PCODE ADM1_EN ADM1_TH ADM1_PCODE ADM0_EN ADM0_TH ADM0_PCODE
1 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
2 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
3 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
4 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
5 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
6 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
7 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
8 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
9 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
10 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
date validOn validTo geometry
1 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.4945 13...
2 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5013 13...
3 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5014 13...
4 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5055 13...
5 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.4987 13...
6 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.502 13....
7 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5057 13...
8 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5002 13...
9 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.4986 13...
10 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5077 13...Code
saveRDS(bmr_3,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_3.rds")Code
bmr_3 <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_3.rds")
head(bmr_3)Simple feature collection with 6 features and 22 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 100.4876 ymin: 13.73863 xmax: 100.5055 ymax: 13.76193
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM3_EN ADM3_TH ADM3_PCODE
1 0.04769920 1.284175e-04 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101
2 0.03355050 6.068479e-05 Wang Burapha Phirom วังบูรพาภิรมย์ TH100102
3 0.01728931 1.769761e-05 Wat Ratchabophit วัดราชบพิธ TH100103
4 0.01904576 1.920433e-05 Samran Rat สำราญราษฎร์ TH100104
5 0.01523190 1.257312e-05 San Chaopho Suea ศาลเจ้าพ่อเสือ TH100105
6 0.01456981 1.292603e-05 Sao Chingcha เสาชิงช้า TH100106
ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH ADM3ALT2TH ADM2_EN ADM2_TH
1 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
2 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
3 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
4 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
5 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
6 <NA> <NA> <NA> <NA> <NA> Phra Nakhon พระนคร
ADM2_PCODE ADM1_EN ADM1_TH ADM1_PCODE ADM0_EN ADM0_TH ADM0_PCODE
1 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
2 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
3 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
4 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
5 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
6 TH1001 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
date validOn validTo geometry
1 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.4945 13...
2 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5013 13...
3 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5014 13...
4 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.5055 13...
5 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.4987 13...
6 2019-02-18 2022-01-22 <NA> MULTIPOLYGON (((100.502 13....This process selects administrative boundaries at the third level (e.g., districts or subdistricts) for the specified cities within the Bangkok Metropolitan Region (BMR) by filtering the dataset for these cities: Bangkok, Nakhon Pathom, Pathum Thani, Nonthaburi, Samut Prakan, and Samut Prakan.
3.3.8 Assign administrative division codes to accident data
Code
# Load the accident and administrative boundary data
acc_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/acc.rds")
adm_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bmr_3.rds")
# Convert accident data to an sf object with specified CRS
acc_sf <- st_as_sf(acc_data, coords = c("longitude", "latitude"), crs = 4326)
# Convert administrative boundary data to an sf object with geometry specified
adm_sf <- st_as_sf(adm_data, wkt = "geometry", crs = 4326)
# Ensure both datasets are in the same CRS
adm_sf <- st_transform(adm_sf, st_crs(acc_sf))
# Spatial join to attach administrative information to accident data
acc_with_adm <- st_join(acc_sf, adm_sf[, c("ADM3_EN", "ADM2_EN")])
# Print the resulting spatially joined data
print(acc_with_adm)Simple feature collection with 81376 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: -16183190 ymin: -936.228 xmax: 1200243 ymax: 4918525
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 81,376 × 22
acc_code incident_datetime report_datetime province_th province_en
* <dbl> <dttm> <dttm> <chr> <chr>
1 571905 2019-01-01 00:00:00 2019-01-02 06:11:00 ลพบุรี Loburi
2 3790870 2019-01-01 00:03:00 2020-02-20 13:48:00 อุบลราชธานี Ubon Ratchathani
3 599075 2019-01-01 00:05:00 2019-01-01 10:35:00 ประจวบคีรีขันธ์ Prachuap Khiri …
4 571924 2019-01-01 00:20:00 2019-01-02 05:12:00 เชียงใหม่ Chiang Mai
5 599523 2019-01-01 00:25:00 2019-01-04 09:42:00 นครสวรรค์ Nakhon Sawan
6 571982 2019-01-01 00:30:00 2019-01-07 12:46:00 แม่ฮ่องสอน Mae Hong Son
7 612782 2019-01-01 00:30:00 2019-10-25 14:25:00 ชุมพร Chumphon
8 599235 2019-01-01 00:35:00 2019-01-02 16:23:00 สิงห์บุรี Sing Buri
9 600643 2019-01-01 00:40:00 2019-01-11 10:01:00 สงขลา Songkhla
10 599105 2019-01-01 00:45:00 2019-01-01 10:11:00 ตราด Trat
# ℹ 81,366 more rows
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
bmr_provinces <- c("Bangkok", "Nakhon Pathom", "Pathum Thani", "Nonthaburi", "Samut Prakan", "Samut Sakhon")
bmr_acc_data <- acc_with_adm %>%
filter(province_en %in% bmr_provinces)
print(bmr_acc_data)Simple feature collection with 12986 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 591277.5 ymin: 1486846 xmax: 710166.1 ymax: 1576520
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 12,986 × 22
acc_code incident_datetime report_datetime province_th province_en
* <dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 600001 2019-01-01 03:00:00 2019-01-05 10:33:00 นนทบุรี Nonthaburi
3 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
4 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
5 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
6 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
7 599990 2019-01-01 05:30:00 2019-01-05 10:35:00 สมุทรสาคร Samut Sakhon
8 612045 2019-01-01 05:30:00 2019-10-09 13:50:00 นนทบุรี Nonthaburi
9 629689 2019-01-01 05:42:00 2019-01-01 05:42:00 กรุงเทพมหานคร Bangkok
10 607046 2019-01-01 06:30:00 2019-05-15 13:24:00 ปทุมธานี Pathum Thani
# ℹ 12,976 more rows
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
write_rds(bmr_acc_data,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/acc.rds")Code
bmr_acc_data <- read_rds("/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/acc.rds")
head(bmr_acc_data)Simple feature collection with 6 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 627012.3 ymin: 1502876 xmax: 693488.9 ymax: 1533381
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 22
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 600001 2019-01-01 03:00:00 2019-01-05 10:33:00 นนทบุรี Nonthaburi
3 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
4 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
5 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
6 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
bmr_acc_data_time <- bmr_acc_data %>%
mutate(incident_datetime = ymd_hms(incident_datetime))Warning: There was 1 warning in `stopifnot()`.
ℹ In argument: `incident_datetime = ymd_hms(incident_datetime)`.
Caused by warning:
! 16 failed to parse.Code
bmr_acc_data_time <- bmr_acc_data_time %>%
mutate(time_period = case_when(
hour(incident_datetime) >= 5 & hour(incident_datetime) < 10 ~ "5-9",
hour(incident_datetime) >= 10 & hour(incident_datetime) < 17 ~ "10-16",
hour(incident_datetime) >= 17 & hour(incident_datetime) < 21 ~ "17-20",
(hour(incident_datetime) >= 21 & hour(incident_datetime) <= 23) | (hour(incident_datetime) >= 0 & hour(incident_datetime) < 5) ~ "21-4"
))
head(bmr_acc_data_time)Simple feature collection with 6 features and 22 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 627012.3 ymin: 1502876 xmax: 693488.9 ymax: 1533381
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 23
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 600001 2019-01-01 03:00:00 2019-01-05 10:33:00 นนทบุรี Nonthaburi
3 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
4 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
5 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
6 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
# ℹ 18 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>, time_period <chr>This process reads two datasets: accident data (bmr_acc_data.rds) and administrative boundary data (bmr_3.rds). Using the sf package, both datasets are converted to spatial formats, with the accident data set to geographic coordinates and the administrative boundaries transformed to a matching coordinate reference system (CRS). A spatial join is then applied to append administrative names (ADM3_EN and ADM2_EN) to the accident data based on location. Finally, the dataset is filtered to include only accidents within the specified provinces of the Bangkok Metropolitan Region (BMR).
3.3.9 Select the boundary of the four most accident-prone cities
Code
bangkok_boundary <- bmr_city %>%
filter(ADM1_EN == "Bangkok")
pathum_thani_boundary <- bmr_city %>%
filter(ADM1_EN == "Pathum Thani")
Samut_Prakan_boundary <- bmr_city %>%
filter(ADM1_EN == "Samut Prakan")
Nakhon_Pathom_boundary <- bmr_city %>%
filter(ADM1_EN == "Nakhon Pathom")
saveRDS(bangkok_boundary,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_boundary.rds")
saveRDS(pathum_thani_boundary,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_boundary.rds")
saveRDS(Samut_Prakan_boundary, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_boundary.rds")
saveRDS(Nakhon_Pathom_boundary, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_boundary.rds")Code
bangkok_boundary <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_boundary.rds")
pathum_thani_boundary <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_boundary.rds")
Samut_Prakan_boundary <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_boundary.rds")
Nakhon_Pathom_boundary <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_boundary.rds")
head(bangkok_boundary)Simple feature collection with 6 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 100.4876 ymin: 13.71808 xmax: 100.9385 ymax: 13.94649
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF ADM2ALT1EN
1 0.08541733 0.0004504685 Phra Nakhon พระนคร TH1001 <NA> <NA>
2 0.13413177 0.0009501914 Dusit ดุสิต TH1002 <NA> <NA>
3 0.67634217 0.0198588627 Nong Chok หนองจอก TH1003 <NA> <NA>
4 0.08588647 0.0003369561 Bang Rak บางรัก TH1004 <NA> <NA>
5 0.30172202 0.0034149298 Bang Khen บางเขน TH1005 <NA> <NA>
6 0.30869124 0.0023032680 Bang Kapi บางกะปิ TH1006 <NA> <NA>
ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH ADM1_PCODE ADM0_EN
1 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
2 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
3 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
4 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
5 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
6 <NA> <NA> <NA> Bangkok กรุงเทพมหานคร TH10 Thailand
ADM0_TH ADM0_PCODE date validOn validTo
1 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((100.5007 13...
2 MULTIPOLYGON (((100.52 13.8...
3 MULTIPOLYGON (((100.914 13....
4 MULTIPOLYGON (((100.517 13....
5 MULTIPOLYGON (((100.61 13.8...
6 MULTIPOLYGON (((100.6291 13...Code
head(pathum_thani_boundary)Simple feature collection with 6 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 100.3316 ymin: 13.91625 xmax: 100.9519 ymax: 14.27595
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF
1 0.6184795 0.011907513 Mueang Pathum Thani เมืองปทุมธานี TH1301 <NA>
2 0.6767629 0.025553518 Khlong Luang คลองหลวง TH1302 <NA>
3 0.7306164 0.009500849 Thanyaburi ธัญบุรี TH1303 <NA>
4 0.7825534 0.028446866 Nong Suea หนองเสือ TH1304 <NA>
5 0.6122519 0.016099675 Lat Lum Kaeo ลาดหลุมแก้ว TH1305 <NA>
6 0.8138248 0.025392078 Lam Luk Ka ลำลูกกา TH1306 <NA>
ADM2ALT1EN ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH ADM1_PCODE
1 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
2 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
3 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
4 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
5 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
6 <NA> <NA> <NA> <NA> Pathum Thani ปทุมธานี TH13
ADM0_EN ADM0_TH ADM0_PCODE date validOn validTo
1 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((100.5944 14...
2 MULTIPOLYGON (((100.7553 14...
3 MULTIPOLYGON (((100.9148 14...
4 MULTIPOLYGON (((100.8916 14...
5 MULTIPOLYGON (((100.3946 14...
6 MULTIPOLYGON (((100.9147 14...Code
head(Samut_Prakan_boundary)Simple feature collection with 6 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 100.4445 ymin: 13.47842 xmax: 100.9639 ymax: 13.71819
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF
1 0.8224170 0.014364807 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 <NA>
2 0.8144705 0.018985669 Bang Bo บางบ่อ TH1102 <NA>
3 0.7792352 0.018316133 Bang Phli บางพลี TH1103 <NA>
4 0.3594240 0.004927183 Phra Pradaeng พระประแดง TH1104 <NA>
5 0.5911512 0.013061732 Phra Samut Chedi พระสมุทรเจดีย์ TH1105 <NA>
6 0.5744135 0.009606464 Bang Sao Thong บางเสาธง TH1106 <NA>
ADM2ALT1EN ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH
1 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
2 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
3 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
4 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
5 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
6 <NA> <NA> <NA> <NA> Samut Prakan สมุทรปราการ
ADM1_PCODE ADM0_EN ADM0_TH ADM0_PCODE date validOn validTo
1 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((100.6013 13...
2 MULTIPOLYGON (((100.9625 13...
3 MULTIPOLYGON (((100.7306 13...
4 MULTIPOLYGON (((100.5795 13...
5 MULTIPOLYGON (((100.564 13....
6 MULTIPOLYGON (((100.8077 13...Code
head(Nakhon_Pathom_boundary)Simple feature collection with 6 features and 19 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 99.8141 ymin: 13.64925 xmax: 100.3375 ymax: 14.17926
Geodetic CRS: WGS 84
Shape_Leng Shape_Area ADM2_EN ADM2_TH ADM2_PCODE ADM2_REF
1 1.1831719 0.03411601 Mueang Nakhon Pathom เมืองนครปฐม TH7301 <NA>
2 1.2689656 0.04034925 Kamphaeng Saen กำแพงแสน TH7302 <NA>
3 0.7743732 0.02180911 Nakhon Chai Si นครชัยศรี TH7303 <NA>
4 0.7564189 0.01257511 Don Tum ดอนตูม TH7304 <NA>
5 1.1866458 0.04548952 Bang Len บางเลน TH7305 <NA>
6 0.9298950 0.01889864 Sam Phran สามพราน TH7306 <NA>
ADM2ALT1EN ADM2ALT2EN ADM2ALT1TH ADM2ALT2TH ADM1_EN ADM1_TH ADM1_PCODE
1 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
2 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
3 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
4 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
5 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
6 <NA> <NA> <NA> <NA> Nakhon Pathom นครปฐม TH73
ADM0_EN ADM0_TH ADM0_PCODE date validOn validTo
1 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 MULTIPOLYGON (((99.95118 13...
2 MULTIPOLYGON (((100.0417 14...
3 MULTIPOLYGON (((100.1792 13...
4 MULTIPOLYGON (((100.1141 14...
5 MULTIPOLYGON (((100.2231 14...
6 MULTIPOLYGON (((100.2598 13...This procedure involves reading two datasets: bmr_acc_data.rds for accident data and bmr_3.rds for administrative boundaries. Both datasets are converted to spatial formats using the sf package, ensuring that the accident data uses geographic coordinates and that the administrative data aligns to the same coordinate reference system (CRS). A spatial join is then executed to attach administrative names (ADM3_EN and ADM2_EN) to the accident data based on geographic location. Finally, the dataset is filtered to retain only accidents occurring within the designated provinces of the Bangkok Metropolitan Region (BMR).
3.3.10 Select the road data of the four cities with the most accidents
Code
pathum_thani_roads <- bmr_roads %>%
filter(ADM1_EN == "Pathum Thani")
bangkok_roads <- bmr_roads %>%
filter(ADM1_EN == "Bangkok")
Samut_Prakan_roads <- bmr_roads %>%
filter(ADM1_EN == "Samut Prakan")
Nakhon_Pathom_roads <- bmr_roads %>%
filter(ADM1_EN == "Nakhon Pathom")
pathum_thani_boundary <- adm_data %>%
filter(ADM1_EN == "Pathum Thani")
bangkok_boundary <- adm_data %>%
filter(ADM1_EN == "Bangkok")
Samut_Prakan_boundary <- adm_data %>%
filter(ADM1_EN == "Samut Prakan")
Nakhon_Pathom_boundary <- adm_data %>%
filter(ADM1_EN == "Nakhon Pathom")
pathum_thani_roads_intersection <- st_intersection(pathum_thani_roads, pathum_thani_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
bangkok_roads_intersection <- st_intersection(bangkok_roads, bangkok_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
Samut_Prakan_roads_intersection <- st_intersection(Samut_Prakan_roads, Samut_Prakan_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
Nakhon_Pathom_roads_intersection <- st_intersection(Nakhon_Pathom_roads, Nakhon_Pathom_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
saveRDS(pathum_thani_roads_intersection, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_roads.rds")
saveRDS(bangkok_roads_intersection, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_roads.rds")
saveRDS(Samut_Prakan_roads_intersection,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_roads_intersection.rds")
saveRDS(Nakhon_Pathom_roads_intersection,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_roads_intersection.rds")Code
pathum_thani_roads_intersection <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_roads.rds")
bangkok_roads_intersection <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_roads.rds")
Samut_Prakan_roads_intersection <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_roads_intersection.rds")
Nakhon_Pathom_roads_intersection <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_roads_intersection.rds")
head(pathum_thani_roads_intersection)Simple feature collection with 6 features and 52 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 100.5244 ymin: 14.01581 xmax: 100.5387 ymax: 14.03009
Geodetic CRS: WGS 84
name name_en highway surface smoothness width lanes oneway
102844 <NA> <NA> primary asphalt <NA> 8 <NA> yes
102907 <NA> <NA> primary asphalt <NA> 8 <NA> yes
103536 <NA> <NA> primary asphalt <NA> <NA> <NA> yes
103537 <NA> <NA> primary asphalt <NA> <NA> <NA> yes
114711 <NA> <NA> primary asphalt <NA> <NA> <NA> yes
441094 ถนนติวานนท์ Tiwanon Road primary asphalt <NA> <NA> <NA> yes
bridge layer source name_th osm_id osm_type Shape_Leng
102844 <NA> <NA> survey <NA> 81881259 ways_line 1.884945
102907 <NA> <NA> GPS;sign <NA> 1175053637 ways_line 1.884945
103536 yes 1 survey <NA> 81896244 ways_line 1.884945
103537 yes 1 GPS;sign <NA> 81896253 ways_line 1.884945
114711 <NA> <NA> GPS;sign <NA> 913249335 ways_line 1.884945
441094 yes 1 survey ถนนติวานนท์ 81871447 ways_line 1.884945
Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
102844 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
102907 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
103536 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
103537 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
114711 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
441094 0.1269834 Pathum Thani ปทุมธานี TH13 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
102844 <NA> <NA> <NA> Thailand ประเทศไทย TH
102907 <NA> <NA> <NA> Thailand ประเทศไทย TH
103536 <NA> <NA> <NA> Thailand ประเทศไทย TH
103537 <NA> <NA> <NA> Thailand ประเทศไทย TH
114711 <NA> <NA> <NA> Thailand ประเทศไทย TH
441094 <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo Shape_Leng.1 Shape_Area.1 ADM3_EN
102844 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
102907 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
103536 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
103537 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
114711 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
441094 2019-02-18 2022-01-22 <NA> 0.1178803 0.0005352867 Bang Prok
ADM3_TH ADM3_PCODE ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH ADM3ALT2TH
102844 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
102907 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
103536 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
103537 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
114711 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
441094 บางปรอก TH130101 <NA> <NA> <NA> <NA> <NA>
ADM2_EN ADM2_TH ADM2_PCODE ADM1_EN.1 ADM1_TH.1
102844 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
102907 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
103536 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
103537 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
114711 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
441094 Mueang Pathum Thani เมืองปทุมธานี TH1301 Pathum Thani ปทุมธานี
ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1 validOn.1
102844 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
102907 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
103536 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
103537 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
114711 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
441094 TH13 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
validTo.1 geometry
102844 <NA> LINESTRING (100.5369 14.027...
102907 <NA> LINESTRING (100.5272 14.030...
103536 <NA> LINESTRING (100.5272 14.029...
103537 <NA> LINESTRING (100.5245 14.030...
114711 <NA> LINESTRING (100.5245 14.015...
441094 <NA> LINESTRING (100.5387 14.026...Code
head(bangkok_roads_intersection)Simple feature collection with 6 features and 52 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 100.4942 ymin: 13.74275 xmax: 100.495 ymax: 13.75728
Geodetic CRS: WGS 84
name name_en highway surface smoothness
116202 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
1105791 <NA> <NA> secondary <NA> <NA>
1105793 <NA> <NA> secondary <NA> <NA>
1366987 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
1570350 ถนนจักรเพชร Chakkraphet Road secondary <NA> <NA>
1573725 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
width lanes oneway bridge layer source name_th osm_id
116202 <NA> 3 yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803646
1105791 <NA> <NA> yes <NA> <NA> <NA> <NA> 1305800725
1105793 <NA> <NA> yes <NA> <NA> <NA> <NA> 1308629713
1366987 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 175803662
1570350 <NA> <NA> <NA> yes 1 <NA> ถนนจักรเพชร 138949585
1573725 <NA> <NA> yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803643
osm_type Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE
116202 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
1105791 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
1105793 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
1366987 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
1570350 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
1573725 ways_line 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10
ADM1_REF ADM1ALT1EN ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH
116202 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
1105791 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
1105793 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
1366987 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
1570350 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
1573725 <NA> <NA> <NA> <NA> <NA> Thailand ประเทศไทย
ADM0_PCODE date validOn validTo Shape_Leng.1 Shape_Area.1
116202 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
1105791 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
1105793 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
1366987 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
1570350 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
1573725 TH 2019-02-18 2022-01-22 <NA> 0.0476992 0.0001284175
ADM3_EN ADM3_TH ADM3_PCODE ADM3_REF ADM3ALT1EN
116202 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
1105791 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
1105793 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
1366987 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
1570350 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
1573725 Phraborom Maharatchawang พระบรมมหาราชวัง TH100101 <NA> <NA>
ADM3ALT2EN ADM3ALT1TH ADM3ALT2TH ADM2_EN ADM2_TH ADM2_PCODE
116202 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
1105791 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
1105793 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
1366987 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
1570350 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
1573725 <NA> <NA> <NA> Phra Nakhon พระนคร TH1001
ADM1_EN.1 ADM1_TH.1 ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1
116202 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
1105791 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
1105793 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
1366987 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
1570350 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
1573725 Bangkok กรุงเทพมหานคร TH10 Thailand ประเทศไทย TH
date.1 validOn.1 validTo.1 geometry
116202 2019-02-18 2022-01-22 <NA> LINESTRING (100.495 13.7571...
1105791 2019-02-18 2022-01-22 <NA> LINESTRING (100.4943 13.747...
1105793 2019-02-18 2022-01-22 <NA> LINESTRING (100.4942 13.747...
1366987 2019-02-18 2022-01-22 <NA> LINESTRING (100.4945 13.756...
1570350 2019-02-18 2022-01-22 <NA> LINESTRING (100.495 13.7427...
1573725 2019-02-18 2022-01-22 <NA> LINESTRING (100.4948 13.757...Code
head(Samut_Prakan_roads_intersection)Simple feature collection with 6 features and 52 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 100.5963 ymin: 13.57623 xmax: 100.61 ymax: 13.59656
Geodetic CRS: WGS 84
name name_en highway surface smoothness width lanes
868560 ถนนศรีนครินทร์ Srinagarindra Road primary <NA> <NA> <NA> 5
887430 ถนนด่านเก่า Dan Kao Road secondary <NA> <NA> <NA> <NA>
1147248 ถนนประโคนชัย Prakhon Chai Road secondary <NA> <NA> <NA> <NA>
1211242 ถนนสายลวด Sai Luat Road secondary asphalt <NA> <NA> 3
1213078 ถนนแพรกษา Phraek Sa Road secondary asphalt <NA> <NA> 3
1406922 ถนนแพรกษา Phraek Sa Road secondary asphalt <NA> <NA> 3
oneway bridge layer source name_th osm_id osm_type Shape_Leng
868560 yes <NA> <NA> <NA> ถนนศรีนครินทร์ 1041598435 ways_line 1.6951
887430 yes <NA> <NA> <NA> ถนนด่านเก่า 1273887881 ways_line 1.6951
1147248 yes <NA> <NA> <NA> ถนนประโคนชัย 154368391 ways_line 1.6951
1211242 yes <NA> <NA> <NA> ถนนสายลวด 1192638442 ways_line 1.6951
1213078 yes yes 1 <NA> ถนนแพรกษา 630810731 ways_line 1.6951
1406922 yes <NA> <NA> <NA> ถนนแพรกษา 630810730 ways_line 1.6951
Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
868560 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
887430 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
1147248 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
1211242 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
1213078 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
1406922 0.07926199 Samut Prakan สมุทรปราการ TH11 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE
868560 <NA> <NA> <NA> Thailand ประเทศไทย TH
887430 <NA> <NA> <NA> Thailand ประเทศไทย TH
1147248 <NA> <NA> <NA> Thailand ประเทศไทย TH
1211242 <NA> <NA> <NA> Thailand ประเทศไทย TH
1213078 <NA> <NA> <NA> Thailand ประเทศไทย TH
1406922 <NA> <NA> <NA> Thailand ประเทศไทย TH
date validOn validTo Shape_Leng.1 Shape_Area.1 ADM3_EN ADM3_TH
868560 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
887430 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
1147248 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
1211242 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
1213078 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
1406922 2019-02-18 2022-01-22 <NA> 0.1536852 0.0007049449 Pak Nam ปากน้ำ
ADM3_PCODE ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH ADM3ALT2TH
868560 TH110101 <NA> <NA> <NA> <NA> <NA>
887430 TH110101 <NA> <NA> <NA> <NA> <NA>
1147248 TH110101 <NA> <NA> <NA> <NA> <NA>
1211242 TH110101 <NA> <NA> <NA> <NA> <NA>
1213078 TH110101 <NA> <NA> <NA> <NA> <NA>
1406922 TH110101 <NA> <NA> <NA> <NA> <NA>
ADM2_EN ADM2_TH ADM2_PCODE ADM1_EN.1 ADM1_TH.1
868560 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
887430 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
1147248 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
1211242 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
1213078 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
1406922 Mueang Samut Prakan เมืองสมุทรปราการ TH1101 Samut Prakan สมุทรปราการ
ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1 validOn.1
868560 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
887430 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
1147248 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
1211242 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
1213078 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
1406922 TH11 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
validTo.1 geometry
868560 <NA> LINESTRING (100.61 13.59632...
887430 <NA> LINESTRING (100.5963 13.596...
1147248 <NA> LINESTRING (100.5969 13.591...
1211242 <NA> LINESTRING (100.6039 13.576...
1213078 <NA> LINESTRING (100.6093 13.586...
1406922 <NA> LINESTRING (100.609 13.5869...Code
head(Nakhon_Pathom_roads_intersection)Simple feature collection with 6 features and 52 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 100.0453 ymin: 13.81526 xmax: 100.0777 ymax: 13.82362
Geodetic CRS: WGS 84
name name_en highway surface smoothness width lanes oneway
41714 ถนนราชวิถี Rat Withi Road secondary <NA> <NA> <NA> <NA> yes
51458 ถนนราชวิถี Rat Withi Road secondary <NA> <NA> <NA> <NA> yes
89255 ถนนเทศา Thesa Road primary <NA> <NA> <NA> <NA> no
267855 ถนนหลังพระ Langphra Road secondary <NA> <NA> <NA> <NA> <NA>
267856 ถนนราชวิถี Rat Withi Road secondary <NA> <NA> <NA> <NA> yes
357264 ถนนพญาพาน Phayaphan Road secondary <NA> <NA> <NA> <NA> yes
bridge layer source name_th osm_id osm_type Shape_Leng Shape_Area
41714 <NA> <NA> <NA> ถนนราชวิถี 96774876 ways_line 2.46303 0.1789142
51458 <NA> <NA> <NA> ถนนราชวิถี 1086851227 ways_line 2.46303 0.1789142
89255 <NA> <NA> <NA> ถนนเทศา 627416534 ways_line 2.46303 0.1789142
267855 <NA> <NA> <NA> ถนนหลังพระ 934172283 ways_line 2.46303 0.1789142
267856 <NA> <NA> <NA> ถนนราชวิถี 934172284 ways_line 2.46303 0.1789142
357264 <NA> <NA> <NA> ถนนพญาพาน 96821442 ways_line 2.46303 0.1789142
ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN ADM1ALT2EN
41714 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
51458 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
89255 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
267855 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
267856 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
357264 Nakhon Pathom นครปฐม TH73 <NA> <NA> <NA>
ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE date
41714 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
51458 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
89255 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
267855 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
267856 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
357264 <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
validOn validTo Shape_Leng.1 Shape_Area.1 ADM3_EN
41714 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
51458 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
89255 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
267855 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
267856 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
357264 2022-01-22 <NA> 0.1035366 0.0003518171 Phra Pathom Chedi
ADM3_TH ADM3_PCODE ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH
41714 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
51458 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
89255 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
267855 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
267856 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
357264 พระปฐมเจดีย์ TH730101 <NA> <NA> <NA> <NA>
ADM3ALT2TH ADM2_EN ADM2_TH ADM2_PCODE ADM1_EN.1
41714 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
51458 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
89255 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
267855 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
267856 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
357264 <NA> Mueang Nakhon Pathom เมืองนครปฐม TH7301 Nakhon Pathom
ADM1_TH.1 ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1
41714 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
51458 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
89255 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
267855 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
267856 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
357264 นครปฐม TH73 Thailand ประเทศไทย TH 2019-02-18
validOn.1 validTo.1 geometry
41714 2022-01-22 <NA> LINESTRING (100.0509 13.816...
51458 2022-01-22 <NA> LINESTRING (100.0453 13.815...
89255 2022-01-22 <NA> LINESTRING (100.0744 13.819...
267855 2022-01-22 <NA> LINESTRING (100.0583 13.817...
267856 2022-01-22 <NA> LINESTRING (100.0585 13.817...
357264 2022-01-22 <NA> LINESTRING (100.0572 13.823...This process filters the road network data for each of the four provinces—Pathum Thani, Bangkok, Samut Prakan, and Nakhon Pathom—within the Bangkok Metropolitan Region (BMR), creating subsets of roads specific to each province. It also filters the administrative boundary data for these same provinces. The road networks for each province are then intersected with their respective boundaries, ensuring that only the road segments within the boundaries of each province are retained for further analysis.
3.3.11 Select the accident data of the four cities with the most accidents
Code
bangkok_acc_data <- bmr_acc_data %>%
filter(province_en == "Bangkok")
pathum_thani_acc_data <- bmr_acc_data %>%
filter(province_en == "Pathum Thani")
Samut_Prakan_acc_data <- bmr_acc_data %>%
filter(province_en == "Samut Prakan")
Nakhon_Pathom_acc_data <- bmr_acc_data %>%
filter(province_en == "Nakhon Pathom")
saveRDS(bangkok_acc_data, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_acc_data.rds")
saveRDS(pathum_thani_acc_data, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_acc_data.rds")
saveRDS(Samut_Prakan_acc_data, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_acc_data.rds")
saveRDS(Nakhon_Pathom_acc_data, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_acc_data.rds")Code
bangkok_acc_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/bangkok_acc_data.rds")
pathum_thani_acc_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/pathum_thani_acc_data.rds")
Samut_Prakan_acc_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Samut_Prakan_acc_data.rds")
Nakhon_Pathom_acc_data <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/Nakhon_Pathom_acc_data.rds")
head(bangkok_acc_data)Simple feature collection with 6 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 645371.9 ymin: 1506578 xmax: 684102 ymax: 1525144
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 22
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
2 629689 2019-01-01 05:42:00 2019-01-01 05:42:00 กรุงเทพมหานคร Bangkok
3 604307 2019-01-01 10:10:00 2019-03-06 10:49:00 กรุงเทพมหานคร Bangkok
4 3793736 2019-01-01 17:30:00 2020-03-11 13:15:00 กรุงเทพมหานคร Bangkok
5 599070 2019-01-01 19:20:00 2019-01-01 20:57:00 กรุงเทพมหานคร Bangkok
6 613605 2019-01-01 21:40:00 2019-11-18 10:57:00 กรุงเทพมหานคร Bangkok
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
head(pathum_thani_acc_data)Simple feature collection with 6 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 646567.4 ymin: 1547213 xmax: 698855.6 ymax: 1562999
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 22
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 607046 2019-01-01 06:30:00 2019-05-15 13:24:00 ปทุมธานี Pathum Thani
2 599343 2019-01-01 09:06:00 2019-01-03 10:16:00 ปทุมธานี Pathum Thani
3 600034 2019-01-01 20:20:00 2019-01-05 10:46:00 ปทุมธานี Pathum Thani
4 605171 2019-01-02 09:00:00 2019-04-02 10:25:00 ปทุมธานี Pathum Thani
5 3792311 2019-01-02 10:54:00 2020-03-04 14:45:00 ปทุมธานี Pathum Thani
6 603695 2019-01-02 18:03:00 2019-02-21 11:34:00 ปทุมธานี Pathum Thani
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
head(Samut_Prakan_acc_data)Simple feature collection with 6 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 664556 ymin: 1502876 xmax: 704436.2 ymax: 1515543
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 22
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
2 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
3 599321 2019-01-01 11:01:00 2019-01-03 13:21:00 สมุทรปราการ Samut Prakan
4 605014 2019-01-01 13:00:00 2019-03-29 08:27:00 สมุทรปราการ Samut Prakan
5 603690 2019-01-01 21:30:00 2019-02-21 14:34:00 สมุทรปราการ Samut Prakan
6 599600 2019-01-02 06:34:00 2019-01-04 09:07:00 สมุทรปราการ Samut Prakan
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>Code
head(Nakhon_Pathom_acc_data)Simple feature collection with 6 features and 21 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 606111.6 ymin: 1520835 xmax: 641347.8 ymax: 1533381
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 22
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
3 599074 2019-01-01 12:00:00 2019-01-01 13:36:00 นครปฐม Nakhon Pathom
4 608962 2019-01-02 20:20:00 2019-07-25 14:07:00 นครปฐม Nakhon Pathom
5 603951 2019-01-06 02:45:00 2019-02-27 09:54:00 นครปฐม Nakhon Pathom
6 603952 2019-01-06 05:00:00 2019-02-27 09:53:00 นครปฐม Nakhon Pathom
# ℹ 17 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>his process filters the accident data for each of the four provinces within the Bangkok Metropolitan Region (BMR)—Bangkok, Pathum Thani, Samut Prakan, and Nakhon Pathom—creating subsets of accident data specific to each province.
4.Visualize analysis
4.1 Visualization of roads and traffic accidents
Code
ggplot() +
geom_sf(data = bmr_roads, color = "black", size = 0.5) +
geom_sf(data = bmr_acc_data, color = "red", size = 2, alpha = 0.6) +
labs(title = "BMR Roads and Accident Locations") +
theme_minimal()
The visualization presents the road network (black) alongside accident locations (red) within the Bangkok Metropolitan Region (BMR). Accidents are dispersed across the area, with noticeable clusters along main roads and highways, particularly in central zones and areas with dense road connections. These clusters suggest a higher accident frequency in high-traffic regions, highlighting specific accident-prone zones that may benefit from focused safety interventions. This pattern points to a strong correlation between traffic volume and accident incidence.
4.2 Visualization of accident severity grading
Code
bmr_acc_data <- bmr_acc_data %>%
mutate(accident_severity = case_when(
number_of_fatalities == 0 & number_of_injuries == 0 ~ "Minor Accident",
number_of_fatalities == 0 & number_of_injuries >= 1 & number_of_injuries <= 3 ~ "Few Injuries",
number_of_fatalities == 0 & number_of_injuries >= 4 & number_of_injuries <= 10 ~ "Moderate Injuries",
number_of_fatalities == 0 & number_of_injuries > 10 ~ "Mass Casualties",
number_of_fatalities > 0 ~ "Fatal Accident"
))
head(bmr_acc_data)Simple feature collection with 6 features and 22 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 627012.3 ymin: 1502876 xmax: 693488.9 ymax: 1533381
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 6 × 23
acc_code incident_datetime report_datetime province_th province_en
<dbl> <dttm> <dttm> <chr> <chr>
1 571882 2019-01-01 02:25:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
2 600001 2019-01-01 03:00:00 2019-01-05 10:33:00 นนทบุรี Nonthaburi
3 605043 2019-01-01 03:00:00 2019-03-29 08:22:00 สมุทรปราการ Samut Prakan
4 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
5 571887 2019-01-01 04:30:00 2019-01-02 17:32:00 นครปฐม Nakhon Pathom
6 599234 2019-01-01 04:45:00 2019-01-02 08:28:00 สมุทรปราการ Samut Prakan
# ℹ 18 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# geometry <POINT [m]>, ADM3_EN <chr>, ADM2_EN <chr>, accident_severity <chr>In this step, road accidents in the Bangkok Metropolitan Region are categorized by severity levels, including classifications like minor accidents, few injuries, moderate injuries, mass casualties, and fatal accidents. This categorization provides a clearer view of the severity distribution within the dataset, facilitating a deeper understanding of accident impact across the region.
Code
colnames(bmr_acc_data) [1] "acc_code" "incident_datetime"
[3] "report_datetime" "province_th"
[5] "province_en" "agency"
[7] "route" "vehicle_type"
[9] "presumed_cause" "accident_type"
[11] "number_of_vehicles_involved" "number_of_fatalities"
[13] "number_of_injuries" "weather_condition"
[15] "road_description" "slope_description"
[17] "Month_num" "Month_fac"
[19] "dayofweek" "geometry"
[21] "ADM3_EN" "ADM2_EN"
[23] "accident_severity" Code
bmr_acc_data$year_month <- format(as.Date(bmr_acc_data$incident_datetime), "%Y-%m")
bmr_acc_data_summary <- bmr_acc_data %>%
group_by(year_month, accident_severity) %>%
summarise(count = n())`summarise()` has grouped output by 'year_month'. You can override using the
`.groups` argument.Code
bmr_acc_data_summary$year_month <- as.Date(paste0(bmr_acc_data_summary$year_month, "-01"))
ggplot(bmr_acc_data_summary, aes(x = year_month, y = count, color = accident_severity, group = accident_severity)) +
geom_line() +
geom_point() +
scale_x_date(date_labels = "%Y", date_breaks = "1 year") + # x轴上只显示年份
labs(title = "Accident Severity Over Time",
x = "Year",
y = "Accident Count",
color = "Accident Severity") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This visualization displays the trend of road accident severity over time from 2019 to 2023. The accident severity categories are represented with different colors, showing the number of incidents for each type per time period. The chart reveals that “Few Injuries” and “Minor Accidents” are the most common types, with fluctuating but generally increasing trends, especially in recent years. “Fatal Accidents” and “Moderate Injuries” remain relatively lower in occurrence, with slight variations over time. The trend for “Mass Casualties” is consistently low but stable. Overall, there is a visible increase in accident severity over time, particularly for the categories with fewer injuries and minor accidents. This suggests a rising trend in accident occurrences with relatively fewer severe outcomes, but the persistence of fatal and moderate injury accidents signals ongoing safety concerns.
4.3 Visualization analysis of accident causes
Code
bmr_acc_data_1 <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/TakeHome_EX01/acc.rds")
bmr_acc_data <- bmr_acc_data_1 %>%
mutate(incident_datetime = ymd_hms(incident_datetime),
year_month = format(incident_datetime, "%Y-%m")) %>%
drop_na(year_month) Warning: There was 1 warning in `stopifnot()`.
ℹ In argument: `incident_datetime = ymd_hms(incident_datetime)`.
Caused by warning:
! 16 failed to parse.Code
bmr_acc_summary <- bmr_acc_data %>%
group_by(year_month, presumed_cause) %>%
summarise(accidents = n()) `summarise()` has grouped output by 'year_month'. You can override using the
`.groups` argument.Code
gg <- ggplot(bmr_acc_summary,
aes(x = year_month,
y = accidents,
size = accidents,
color = presumed_cause,
frame = year_month)) +
geom_point(alpha = 0.7) +
labs(title = "Accidents by Presumed Cause Over Time",
x = NULL,
y = "Accident Count") +
scale_size(range = c(2, 10)) +
theme_minimal() +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank()) +
guides(color = guide_legend(override.aes = list(size = 5)))
ggplotly(gg) %>%
style(hoverinfo = "text") Warning in p$x$data[firstFrame] <- p$x$frames[[1]]$data: number of items to
replace is not a multiple of replacement lengthThese visualizations depict road accidents over time, categorized by presumed causes such as speeding, tailgating, illegal overtaking, and running red lights. The size of the bubbles represents the frequency of accidents attributed to each cause. Over the course of the animation, we observe several key trends:
Speeding consistently appears as a major cause, represented by larger bubbles throughout the timeline, indicating its prominent role in accidents.
Other causes, such as running red lights and illegal overtaking, also maintain steady but lower frequencies, as shown by smaller bubbles
4.4 Visualization of the third-level administrative divisions
Code
bmr_acc_data <- st_transform(bmr_acc_data, crs = st_crs(bmr_3))
bmr_acc_data_summary <- bmr_acc_data %>%
group_by(ADM3_EN) %>%
summarize(accidents = n())
bmr_3_summary <- st_join(bmr_3, bmr_acc_data_summary, join = st_intersects)
map <- tm_shape(bmr_3_summary) +
tm_borders() +
tm_fill("accidents", palette = "YlOrRd", title = "Accident Count") +
tm_layout(title = "BMR Accident Distribution by ADM3_EN", title.size = 1.5)
print(map)
This map shows the distribution of road accidents across different administrative zones in the Bangkok Metropolitan Region, with darker shades representing higher accident counts. Central areas, especially in high-traffic zones, exhibit the highest accident concentrations, while peripheral regions have fewer incidents. The visualization highlights significant geographical variability in accident rates, suggesting a need for targeted safety measures in accident-prone areas, particularly in the central parts of the region.
5.Network KDE (NKDE) Analysis
5.1 Data Processing
5.1.1 Convert to LINESTRING format
Code
target_crs <- 32647 # UTM Zone 47N
bangkok_acc_data <- st_transform(bangkok_acc_data, crs = target_crs)
bangkok_roads_intersection <- st_transform(bangkok_roads_intersection, crs = target_crs)
bangkok_boundary <- st_transform(bangkok_boundary, crs = target_crs)
acc_in_bangkok <- st_intersection(bangkok_acc_data, bangkok_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
roads_in_bangkok <- st_intersection(bangkok_roads_intersection, bangkok_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
roads_in_bangkok <- roads_in_bangkok %>%
filter(st_geometry_type(roads_in_bangkok) %in% c("LINESTRING", "MULTILINESTRING"))
roads_in_bangkok <- st_cast(roads_in_bangkok, "LINESTRING", group_or_split = TRUE)Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyWarning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
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[10165] LINESTRING LINESTRING LINESTRING LINESTRING
18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLECode
# 确定目标坐标系为 UTM Zone 47N (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 将事故数据和道路数据转换为 UTM 坐标系
pathum_thani_acc_data <- st_transform(pathum_thani_acc_data, crs = target_crs)
pathum_thani_roads_intersection <- st_transform(pathum_thani_roads_intersection, crs = target_crs)
pathum_thani_boundary <- st_transform(pathum_thani_boundary, crs = target_crs)
# 执行空间相交操作（剪切）
acc_in_pathum_thani <- st_intersection(pathum_thani_acc_data, pathum_thani_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
roads_in_pathum_thani <- st_intersection(pathum_thani_roads_intersection, pathum_thani_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
# 过滤出 LINESTRING 和 MULTILINESTRING 类型的几何对象
roads_in_pathum_thani <- roads_in_pathum_thani %>%
filter(st_geometry_type(roads_in_pathum_thani) %in% c("LINESTRING", "MULTILINESTRING"))
# 将 MULTILINESTRING 转换为多个 LINESTRING，保留所有线段
roads_in_pathum_thani <- st_cast(roads_in_pathum_thani, "LINESTRING", group_or_split = TRUE)Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyWarning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
# 检查转换成功与否，应该显示为 LINESTRING
st_geometry_type(roads_in_pathum_thani) [1] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[7] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[13] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[19] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLECode
# 确定目标坐标系为 UTM Zone 47N (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 将事故数据和道路数据转换为 UTM 坐标系
Samut_Prakan_acc_data <- st_transform(Samut_Prakan_acc_data, crs = target_crs)
Samut_Prakan_roads_intersection <- st_transform(Samut_Prakan_roads_intersection, crs = target_crs)
Samut_Prakan_boundary <- st_transform(Samut_Prakan_boundary, crs = target_crs)
# 执行空间相交操作（剪切）
acc_in_Samut_Prakan <- st_intersection(Samut_Prakan_acc_data, Samut_Prakan_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
roads_in_Samut_Prakan <- st_intersection(Samut_Prakan_roads_intersection, Samut_Prakan_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
# 过滤出 LINESTRING 和 MULTILINESTRING 类型的几何对象
roads_in_Samut_Prakan <- roads_in_Samut_Prakan %>%
filter(st_geometry_type(roads_in_Samut_Prakan) %in% c("LINESTRING", "MULTILINESTRING"))
# 将 MULTILINESTRING 转换为多个 LINESTRING，保留所有线段
roads_in_Samut_Prakan <- st_cast(roads_in_Samut_Prakan, "LINESTRING", group_or_split = TRUE)Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyWarning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
# 检查转换成功与否，应该显示为 LINESTRING
st_geometry_type(roads_in_Samut_Prakan) [1] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[7] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[13] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[19] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[25] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[31] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[673] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[679] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[685] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[691] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[697] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[709] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[715] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[727] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[745] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[805] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[841] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[847] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[853] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[859] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[865] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[871] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[877] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[883] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[889] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[901] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[925] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[991] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[997] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1111] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1273] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1291] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1297] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1303] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1309] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1387] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1405] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1435] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1603] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1615] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1699] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1705] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1711] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1717] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1723] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1729] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1735] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1741] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[1765] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1771] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1777] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1783] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1789] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1795] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1801] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1807] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1813] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1819] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1825] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1831] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1837] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1843] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1849] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1855] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1861] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1867] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1873] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1879] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1885] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1891] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1897] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1903] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1909] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1915] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1921] LINESTRING LINESTRING LINESTRING
18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLECode
# 确定目标坐标系为 UTM Zone 47N (EPSG: 32647)
target_crs <- 32647 # UTM Zone 47N
# 将事故数据和道路数据转换为 UTM 坐标系
Nakhon_Pathom_acc_data <- st_transform(Nakhon_Pathom_acc_data, crs = target_crs)
Nakhon_Pathom_roads_intersection <- st_transform(Nakhon_Pathom_roads_intersection, crs = target_crs)
Nakhon_Pathom_boundary <- st_transform(Nakhon_Pathom_boundary, crs = target_crs)
# 执行空间相交操作（剪切）
acc_in_Nakhon_Pathom <- st_intersection(Nakhon_Pathom_acc_data, Nakhon_Pathom_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
roads_in_Nakhon_Pathom <- st_intersection(Nakhon_Pathom_roads_intersection, Nakhon_Pathom_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
# 过滤出 LINESTRING 和 MULTILINESTRING 类型的几何对象
roads_in_Nakhon_Pathom <- roads_in_Nakhon_Pathom %>%
filter(st_geometry_type(roads_in_Nakhon_Pathom) %in% c("LINESTRING", "MULTILINESTRING"))
# 将 MULTILINESTRING 转换为多个 LINESTRING，保留所有线段
roads_in_Nakhon_Pathom <- st_cast(roads_in_Nakhon_Pathom, "LINESTRING", group_or_split = TRUE)Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyWarning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
# 检查转换成功与否，应该显示为 LINESTRING
st_geometry_type(roads_in_Nakhon_Pathom) [1] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[7] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[13] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[19] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[25] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[31] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[37] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[43] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[49] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[55] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[61] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[67] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[73] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[79] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[85] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[91] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[97] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[103] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[109] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[115] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[121] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[127] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[133] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[139] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[145] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[151] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[157] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[163] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[169] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[175] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[181] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[187] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[193] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[199] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[205] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[211] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[217] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[223] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[229] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[235] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[241] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[247] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[253] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[259] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[265] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[271] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[277] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[283] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[289] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[295] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[301] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[307] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[313] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[325] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[331] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[337] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[343] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[349] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[355] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[361] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[367] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[373] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[379] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[385] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[391] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[397] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[403] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[409] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[415] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[421] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[427] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[433] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[439] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[445] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[451] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[457] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[463] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[469] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[475] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[481] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[487] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[493] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[499] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[505] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[511] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[517] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[523] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[529] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[535] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[541] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[547] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[553] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[559] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[565] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[571] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[577] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[583] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[589] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[595] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[601] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[607] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[613] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[619] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[625] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[631] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[637] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[643] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[649] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[655] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[661] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[667] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[673] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[679] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[685] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[691] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[697] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[703] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[709] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[715] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[721] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[727] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[745] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[751] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[757] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[763] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[775] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[781] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[793] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[805] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[811] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[817] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[823] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[835] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[841] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[847] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[853] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[859] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
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[871] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[877] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[883] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[889] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[895] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[901] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[907] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[913] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[919] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[925] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[931] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[937] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[943] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[949] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[955] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[961] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[967] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[973] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[979] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[985] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[991] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[997] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1003] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1009] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1015] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1021] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1027] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1033] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1039] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1045] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1051] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1057] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1063] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1069] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1075] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1081] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1087] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1093] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1099] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1105] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1111] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1117] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1123] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1129] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1135] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1141] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1147] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1153] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1159] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1165] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1171] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1177] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1183] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1189] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1195] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1201] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1207] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1213] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1219] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1225] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1231] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1237] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1243] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1249] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1255] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1261] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1267] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1273] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1279] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1285] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1291] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1297] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1303] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1309] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1315] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1321] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1327] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1333] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1339] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1345] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1351] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1357] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1363] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1369] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1375] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1381] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1387] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1393] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1399] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1405] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1411] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1417] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1423] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1429] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1435] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1441] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1447] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1453] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1459] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1465] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1471] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1477] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1483] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1489] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1495] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1501] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1507] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1513] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1519] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1525] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1531] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1537] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1543] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1549] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1555] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1561] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1567] LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING LINESTRING
[1573] LINESTRING LINESTRING LINESTRING
18 Levels: GEOMETRY POINT LINESTRING POLYGON MULTIPOINT ... TRIANGLECode
saveRDS(roads_in_bangkok, "/Users/yuhu/Desktop/roads")
saveRDS(roads_in_Samut_Prakan, "/Users/yuhu/Desktop/roads_in_Samut_Prakan.rds")
saveRDS(roads_in_pathum_thani, "/Users/yuhu/Desktop/roads_in_pathum_thani.rds")
saveRDS(roads_in_Nakhon_Pathom, "/Users/yuhu/Desktop/roads_in_Nakhon_Pathom.rds")This step transforms accident and road network data for multiple regions (Bangkok, Pathum Thani, Samut Prakan, and Nakhon Pathom) into a common coordinate reference system for consistency in spatial analysis. It then performs spatial intersections to clip the accident and road data to the boundaries of each respective region, ensuring that only data within these boundaries are retained. Finally, the road data is refined to retain only LINESTRING geometries, converting any MULTILINESTRING geometries into individual LINESTRING segments for more accurate spatial representation.
5.1.2 Preparing the lixels objects
Code
saveRDS(roads_in_bangkok,"/Users/yuhu/Desktop/roads_in_bangkok.rds")Code
roads_in_bangkok <- readRDS("/Users/yuhu/Desktop/roads_in_bangkok.rds")Code
target_crs <- 32647
bmr_acc_data <- st_transform(bmr_acc_data, crs = target_crs)
bmr_boundary <- st_transform(bmr_boundary, crs = target_crs)
acc_in_bmr <- st_intersection(bmr_acc_data, bmr_boundary)Warning: attribute variables are assumed to be spatially constant throughout
all geometriesCode
print(acc_in_bmr)Simple feature collection with 12970 features and 38 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 591277.5 ymin: 1486846 xmax: 710166.1 ymax: 1576520
Projected CRS: WGS 84 / UTM zone 47N
# A tibble: 12,970 × 39
acc_code incident_datetime report_datetime province_th province_en
* <dbl> <dttm> <dttm> <chr> <chr>
1 629691 2019-01-01 03:05:00 2019-01-01 03:05:00 กรุงเทพมหานคร Bangkok
2 629689 2019-01-01 05:42:00 2019-01-01 05:42:00 กรุงเทพมหานคร Bangkok
3 604307 2019-01-01 10:10:00 2019-03-06 10:49:00 กรุงเทพมหานคร Bangkok
4 3793736 2019-01-01 17:30:00 2020-03-11 13:15:00 กรุงเทพมหานคร Bangkok
5 599070 2019-01-01 19:20:00 2019-01-01 20:57:00 กรุงเทพมหานคร Bangkok
6 613605 2019-01-01 21:40:00 2019-11-18 10:57:00 กรุงเทพมหานคร Bangkok
7 615219 2019-01-01 22:15:00 2019-12-27 10:12:00 กรุงเทพมหานคร Bangkok
8 613557 2019-01-01 23:05:00 2019-11-18 10:57:00 กรุงเทพมหานคร Bangkok
9 629699 2019-01-02 03:40:00 2019-01-02 03:40:00 กรุงเทพมหานคร Bangkok
10 3793707 2019-01-02 07:00:00 2020-03-11 12:57:00 กรุงเทพมหานคร Bangkok
# ℹ 12,960 more rows
# ℹ 34 more variables: agency <chr>, route <chr>, vehicle_type <chr>,
# presumed_cause <chr>, accident_type <chr>,
# number_of_vehicles_involved <dbl>, number_of_fatalities <dbl>,
# number_of_injuries <dbl>, weather_condition <chr>, road_description <chr>,
# slope_description <chr>, Month_num <dbl>, Month_fac <ord>, dayofweek <chr>,
# ADM3_EN <chr>, ADM2_EN <chr>, year_month <chr>, Shape_Leng <dbl>, …Code
saveRDS(acc_in_pathum_thani,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_pathum_thani.rds")
saveRDS(acc_in_bangkok,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_bangkok.rds")
saveRDS(acc_in_Samut_Prakan, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_Samut_Prakan.rds")
saveRDS(acc_in_Nakhon_Pathom, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_Nakhon_Pathom.rds")Code
acc_in_bangkok <-readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_bangkok.rds")
acc_in_pathum_thani <-readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_pathum_thani.rds")
acc_in_Samut_Prakan <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_Samut_Prakan.rds")
acc_in_Nakhon_Pathom <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/acc_in_Nakhon_Pathom.rds")Code
roads_in_bangkok_lines <- st_cast(roads_in_bangkok, "LINESTRING")
lixels_bangkok <- lixelize_lines(roads_in_bangkok_lines,
10000,
mindist = 5000)
samples_bangkok <- lines_center(lixels_bangkok)Code
roads_in_pathum_thani_lines <- st_cast(pathum_thani_roads_intersection, "LINESTRING")Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
lixels_pathum_thani <- lixelize_lines(roads_in_pathum_thani_lines,
10000,
mindist = 5000)
samples_pathum_thani <- lines_center(lixels_pathum_thani)Code
roads_in_Samut_Prakan_lines <- st_cast(Samut_Prakan_roads_intersection, "LINESTRING")Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
lixels_Samut_Prakan <- lixelize_lines(roads_in_Samut_Prakan_lines,
10000,
mindist = 5000)
samples_Samut_Prakan <- lines_center(lixels_Samut_Prakan)Code
roads_in_Nakhon_Pathom_lines <- st_cast(Nakhon_Pathom_roads_intersection, "LINESTRING")Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring only
Warning in st_cast.MULTILINESTRING(X[[i]], ...): keeping first linestring onlyCode
lixels_Nakhon_Pathom <- lixelize_lines(roads_in_Nakhon_Pathom_lines,
10000,
mindist = 5000)
samples_Nakhon_Pathom <- lines_center(lixels_Nakhon_Pathom)Code
print(lixels_bangkok)Simple feature collection with 10168 features and 75 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 643873.2 ymin: 1494987 xmax: 709106.9 ymax: 1543267
Projected CRS: WGS 84 / UTM zone 47N
First 10 features:
lineID name name_en highway surface smoothness
1 1 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
2 2 <NA> <NA> secondary <NA> <NA>
3 3 <NA> <NA> secondary <NA> <NA>
4 4 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
5 5 ถนนจักรเพชร Chakkraphet Road secondary <NA> <NA>
6 6 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
7 7 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
8 8 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
9 9 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
10 10 ถนนสนามไชย Sanam Chai Road secondary asphalt <NA>
width lanes oneway bridge layer source name_th osm_id osm_type
1 <NA> 3 yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803646 ways_line
2 <NA> <NA> yes <NA> <NA> <NA> <NA> 1305800725 ways_line
3 <NA> <NA> yes <NA> <NA> <NA> <NA> 1308629713 ways_line
4 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 175803662 ways_line
5 <NA> <NA> <NA> yes 1 <NA> ถนนจักรเพชร 138949585 ways_line
6 <NA> <NA> yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803643 ways_line
7 <NA> 3 yes <NA> <NA> <NA> ถนนราชดำเนินใน 25715079 ways_line
8 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 162363628 ways_line
9 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 25715087 ways_line
10 <NA> <NA> <NA> <NA> <NA> <NA> ถนนสนามไชย 162625798 ways_line
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
1 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
2 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
3 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
4 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
5 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
6 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
7 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
8 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
9 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
10 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE date
1 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
2 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
3 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
4 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
5 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
6 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
7 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
8 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
9 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
10 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
validOn validTo Shape_Leng.1 Shape_Area.1 ADM3_EN
1 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
2 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
3 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
4 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
5 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
6 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
7 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
8 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
9 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
10 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
ADM3_TH ADM3_PCODE ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH
1 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
2 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
3 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
4 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
5 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
6 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
7 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
8 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
9 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
10 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
ADM3ALT2TH ADM2_EN ADM2_TH ADM2_PCODE ADM1_EN.1 ADM1_TH.1
1 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
2 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
3 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
4 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
5 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
6 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
7 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
8 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
9 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
10 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1 validOn.1
1 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
2 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
3 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
4 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
5 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
6 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
7 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
8 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
9 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
10 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
validTo.1 Shape_Leng.2 Shape_Area.2 ADM3_EN.1 ADM3_TH.1
1 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
2 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
3 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
4 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
5 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
6 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
7 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
8 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
9 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
10 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
ADM3_PCODE.1 ADM3_REF.1 ADM3ALT1EN.1 ADM3ALT2EN.1 ADM3ALT1TH.1 ADM3ALT2TH.1
1 TH100101 <NA> <NA> <NA> <NA> <NA>
2 TH100101 <NA> <NA> <NA> <NA> <NA>
3 TH100101 <NA> <NA> <NA> <NA> <NA>
4 TH100101 <NA> <NA> <NA> <NA> <NA>
5 TH100101 <NA> <NA> <NA> <NA> <NA>
6 TH100101 <NA> <NA> <NA> <NA> <NA>
7 TH100101 <NA> <NA> <NA> <NA> <NA>
8 TH100101 <NA> <NA> <NA> <NA> <NA>
9 TH100101 <NA> <NA> <NA> <NA> <NA>
10 TH100101 <NA> <NA> <NA> <NA> <NA>
ADM2_EN.1 ADM2_TH.1 ADM2_PCODE.1 ADM1_EN.2 ADM1_TH.2 ADM1_PCODE.2
1 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
2 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
3 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
4 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
5 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
6 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
7 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
8 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
9 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
10 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
ADM0_EN.2 ADM0_TH.2 ADM0_PCODE.2 date.2 validOn.2 validTo.2
1 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
7 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
8 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
9 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 LINESTRING (661630.6 152136...
2 LINESTRING (661558.8 152030...
3 LINESTRING (661549.2 152029...
4 LINESTRING (661577.3 152129...
5 LINESTRING (661639.2 151977...
6 LINESTRING (661606.9 152137...
7 LINESTRING (661613 1521351,...
8 LINESTRING (661582.6 152132...
9 LINESTRING (661599.3 152136...
10 LINESTRING (661501.9 152069...Code
print(samples_bangkok)Simple feature collection with 10168 features and 75 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 644080.6 ymin: 1495170 xmax: 709089.5 ymax: 1543230
Projected CRS: WGS 84 / UTM zone 47N
First 10 features:
lineID name name_en highway surface smoothness
1 1 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
2 2 <NA> <NA> secondary <NA> <NA>
3 3 <NA> <NA> secondary <NA> <NA>
4 4 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
5 5 ถนนจักรเพชร Chakkraphet Road secondary <NA> <NA>
6 6 สะพานผ่านพิภพลีลา Phan Phiphop Lila Bridge secondary asphalt <NA>
7 7 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
8 8 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
9 9 ถนนราชดำเนินใน Ratchadamnoen Nai Road secondary asphalt <NA>
10 10 ถนนสนามไชย Sanam Chai Road secondary asphalt <NA>
width lanes oneway bridge layer source name_th osm_id osm_type
1 <NA> 3 yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803646 ways_line
2 <NA> <NA> yes <NA> <NA> <NA> <NA> 1305800725 ways_line
3 <NA> <NA> yes <NA> <NA> <NA> <NA> 1308629713 ways_line
4 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 175803662 ways_line
5 <NA> <NA> <NA> yes 1 <NA> ถนนจักรเพชร 138949585 ways_line
6 <NA> <NA> yes yes 1 <NA> สะพานผ่านพิภพลีลา 175803643 ways_line
7 <NA> 3 yes <NA> <NA> <NA> ถนนราชดำเนินใน 25715079 ways_line
8 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 162363628 ways_line
9 <NA> <NA> yes <NA> <NA> <NA> ถนนราชดำเนินใน 25715087 ways_line
10 <NA> <NA> <NA> <NA> <NA> <NA> ถนนสนามไชย 162625798 ways_line
Shape_Leng Shape_Area ADM1_EN ADM1_TH ADM1_PCODE ADM1_REF ADM1ALT1EN
1 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
2 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
3 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
4 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
5 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
6 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
7 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
8 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
9 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
10 2.417227 0.1313387 Bangkok กรุงเทพมหานคร TH10 <NA> <NA>
ADM1ALT2EN ADM1ALT1TH ADM1ALT2TH ADM0_EN ADM0_TH ADM0_PCODE date
1 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
2 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
3 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
4 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
5 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
6 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
7 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
8 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
9 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
10 <NA> <NA> <NA> Thailand ประเทศไทย TH 2019-02-18
validOn validTo Shape_Leng.1 Shape_Area.1 ADM3_EN
1 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
2 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
3 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
4 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
5 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
6 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
7 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
8 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
9 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
10 2022-01-22 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang
ADM3_TH ADM3_PCODE ADM3_REF ADM3ALT1EN ADM3ALT2EN ADM3ALT1TH
1 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
2 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
3 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
4 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
5 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
6 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
7 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
8 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
9 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
10 พระบรมมหาราชวัง TH100101 <NA> <NA> <NA> <NA>
ADM3ALT2TH ADM2_EN ADM2_TH ADM2_PCODE ADM1_EN.1 ADM1_TH.1
1 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
2 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
3 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
4 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
5 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
6 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
7 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
8 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
9 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
10 <NA> Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร
ADM1_PCODE.1 ADM0_EN.1 ADM0_TH.1 ADM0_PCODE.1 date.1 validOn.1
1 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
2 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
3 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
4 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
5 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
6 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
7 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
8 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
9 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
10 TH10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22
validTo.1 Shape_Leng.2 Shape_Area.2 ADM3_EN.1 ADM3_TH.1
1 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
2 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
3 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
4 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
5 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
6 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
7 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
8 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
9 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
10 <NA> 0.0476992 0.0001284175 Phraborom Maharatchawang พระบรมมหาราชวัง
ADM3_PCODE.1 ADM3_REF.1 ADM3ALT1EN.1 ADM3ALT2EN.1 ADM3ALT1TH.1 ADM3ALT2TH.1
1 TH100101 <NA> <NA> <NA> <NA> <NA>
2 TH100101 <NA> <NA> <NA> <NA> <NA>
3 TH100101 <NA> <NA> <NA> <NA> <NA>
4 TH100101 <NA> <NA> <NA> <NA> <NA>
5 TH100101 <NA> <NA> <NA> <NA> <NA>
6 TH100101 <NA> <NA> <NA> <NA> <NA>
7 TH100101 <NA> <NA> <NA> <NA> <NA>
8 TH100101 <NA> <NA> <NA> <NA> <NA>
9 TH100101 <NA> <NA> <NA> <NA> <NA>
10 TH100101 <NA> <NA> <NA> <NA> <NA>
ADM2_EN.1 ADM2_TH.1 ADM2_PCODE.1 ADM1_EN.2 ADM1_TH.2 ADM1_PCODE.2
1 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
2 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
3 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
4 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
5 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
6 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
7 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
8 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
9 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
10 Phra Nakhon พระนคร TH1001 Bangkok กรุงเทพมหานคร TH10
ADM0_EN.2 ADM0_TH.2 ADM0_PCODE.2 date.2 validOn.2 validTo.2
1 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
2 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
3 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
4 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
5 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
6 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
7 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
8 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
9 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
10 Thailand ประเทศไทย TH 2019-02-18 2022-01-22 <NA>
geometry
1 POINT (661626.8 1521363)
2 POINT (661565.6 1520302)
3 POINT (661551.8 1520302)
4 POINT (661580 1521310)
5 POINT (661635.2 1519781)
6 POINT (661610.6 1521381)
7 POINT (661594.2 1521322)
8 POINT (661590.9 1521348)
9 POINT (661603.1 1521372)
10 POINT (661489.6 1520771)Code
saveRDS(lixels_pathum_thani,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_pathum_thani.rds")
saveRDS(samples_pathum_thani,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_pathum_thani.rds")
saveRDS(lixels_bangkok,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_bangkok.rds")
saveRDS(samples_bangkok,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_bangkok.rds")
saveRDS(lixels_Samut_Prakan,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_Samut_Prakan.rds")
saveRDS(samples_Samut_Prakan,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_Samut_Prakan.rds")
saveRDS(lixels_Nakhon_Pathom,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_Nakhon_Pathom.rds")
saveRDS(samples_Nakhon_Pathom,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_Nakhon_Pathom.rds")Code
lixels_bangkok <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_bangkok.rds")
sample_bangkok <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_bangkok.rds")
lixels_pathum_thani <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_pathum_thani.rds")
sample_pathum_thani <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_pathum_thani.rds")
lixels_Samut_Prakan <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_Samut_Prakan.rds")
samples_Samut_Prakan <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_pathum_thani.rds")
lixels_Nakhon_Pathom <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/lixels_Nakhon_Pathom.rds")
samples_Nakhon_Pathom <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/samples_Nakhon_Pathom.rds")This process begins by converting the road network data for each region (Bangkok, Pathum Thani, Samut Prakan, and Nakhon Pathom) into LINESTRING geometries, creating a consistent spatial format. Next, it generates “lixels” (line pixels)—linear segments of 10,000 meters in length—from these road lines. Using the lixelize_lines function, the road network is divided into these segments with a minimum spacing of 5,000 meters. After creating the lixels, the lines_center function extracts the center points of each segment, resulting in sample points along the road network. These points can be utilized for further spatial analysis, such as assessing traffic flow or accident density along specific segments.
5.1.3 Performing NKDE
Code
nkde_result_bangkok <- nkde(
lines = lixels_bangkok,
events = acc_in_bangkok,
w = rep(1, nrow(acc_in_bangkok)),
samples = samples_bangkok,
kernel_name = "quartic",
bw = 500,
div = "bw",
method = "simple",
grid_shape = c(200, 200),
verbose = TRUE
)[1] "checking inputs ..."
[1] "prior data preparation ..."
[1] "Splitting the data with the spatial grid ..."
[1] "start calculating the kernel values ..."
[1] " quadra 1/2725"
[1] " quadra 2/2725"
[1] " quadra 3/2725"
[1] " quadra 4/2725"
[1] " quadra 5/2725"
[1] " quadra 6/2725"
[1] " quadra 7/2725"
[1] " quadra 8/2725"
[1] " quadra 9/2725"
[1] " quadra 10/2725"
[1] " quadra 11/2725"
[1] " quadra 12/2725"
[1] " quadra 13/2725"
[1] " quadra 14/2725"
[1] " quadra 15/2725"
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[1] " quadra 26/2725"
[1] " quadra 27/2725"
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[1] " quadra 30/2725"
[1] " quadra 31/2725"
[1] " quadra 32/2725"
[1] " quadra 33/2725"
[1] " quadra 34/2725"
[1] " quadra 35/2725"
[1] " build graph ..."
[1] " calculating NKDE values ..."
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|======================================================================| 100%[1] " quadra 1718/2725"
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[1] "combining the results ..."Code
nkde_result_pathum_thani <- nkde(
lines = lixels_pathum_thani,
events = acc_in_pathum_thani,
w = rep(1, nrow(acc_in_pathum_thani)),
samples = samples_pathum_thani,
kernel_name = "quartic",
bw = 500,
div = "bw",
method = "simple",
grid_shape = c(200, 200),
verbose = TRUE
)[1] "checking inputs ..."
[1] "prior data preparation ..."
[1] "Splitting the data with the spatial grid ..."
[1] "start calculating the kernel values ..."
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nkde_result_Nakhon_Pathom <- nkde(
lines = lixels_Nakhon_Pathom,
events = acc_in_Nakhon_Pathom,
w = rep(1, nrow(acc_in_Nakhon_Pathom)),
samples = samples_Nakhon_Pathom,
kernel_name = "quartic",
bw = 500,
div = "bw",
method = "simple",
grid_shape = c(200, 200),
verbose = TRUE
)[1] "checking inputs ..."
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print(nkde_result_bangkok) [1] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[6] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[11] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[16] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[21] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[26] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[31] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[36] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[41] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[46] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[51] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[56] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[61] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[66] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[71] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[76] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[81] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[86] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[91] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[96] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[191] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
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[9691] 2.460619e-06 0.000000e+00 1.058811e-05 1.096439e-05 0.000000e+00
[9696] 8.432396e-09 8.390006e-06 2.394743e-06 6.150134e-06 1.080279e-05
[9701] 1.079060e-05 0.000000e+00 0.000000e+00 1.098536e-05 1.001982e-05
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[9761] 2.904723e-06 0.000000e+00 1.956536e-05 9.793531e-06 3.749380e-06
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[9796] 7.207937e-06 3.139727e-05 9.444378e-05 6.508949e-05 1.865195e-05
[9801] 0.000000e+00 1.286764e-05 1.426418e-05 0.000000e+00 4.452011e-05
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[9811] 1.488465e-04 1.433597e-05 3.736745e-06 7.188073e-06 1.278793e-05
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[9821] 0.000000e+00 4.577598e-07 3.718161e-05 1.572644e-05 0.000000e+00
[9826] 0.000000e+00 5.600286e-05 2.141338e-06 6.088608e-05 2.167417e-05
[9831] 0.000000e+00 0.000000e+00 8.598171e-06 1.162441e-05 1.048046e-05
[9836] 0.000000e+00 1.138323e-06 3.978157e-05 0.000000e+00 0.000000e+00
[9841] 0.000000e+00 0.000000e+00 1.488712e-05 6.608242e-05 4.831961e-05
[9846] 4.330620e-05 9.959006e-05 1.185613e-05 2.325748e-05 2.119917e-05
[9851] 2.526570e-05 9.331445e-06 0.000000e+00 0.000000e+00 0.000000e+00
[9856] 0.000000e+00 0.000000e+00 0.000000e+00 1.702283e-05 1.225910e-05
[9861] 0.000000e+00 0.000000e+00 2.475385e-07 1.450685e-05 0.000000e+00
[9866] 0.000000e+00 4.548532e-07 1.702690e-05 6.770124e-06 5.575047e-05
[9871] 0.000000e+00 1.569470e-06 5.446758e-05 3.917894e-05 1.168075e-05
[9876] 3.693003e-05 3.124254e-05 1.885765e-05 9.337287e-06 3.972367e-05
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[9886] 0.000000e+00 1.148387e-05 0.000000e+00 1.517157e-05 0.000000e+00
[9891] 2.972327e-05 7.223287e-05 3.724073e-06 4.905142e-05 8.599100e-06
[9896] 2.235346e-05 1.435608e-05 1.956901e-05 5.549304e-05 3.089834e-05
[9901] 0.000000e+00 0.000000e+00 5.964240e-07 5.642427e-06 1.977589e-05
[9906] 9.572121e-06 0.000000e+00 2.424610e-05 0.000000e+00 0.000000e+00
[9911] 0.000000e+00 1.501823e-05 1.652137e-05 0.000000e+00 6.099422e-05
[9916] 0.000000e+00 4.171912e-05 8.561950e-05 1.483146e-05 1.521746e-05
[9921] 7.437307e-05 2.780350e-05 2.548277e-05 3.739935e-05 5.438291e-06
[9926] 1.259697e-05 1.465208e-05 6.137254e-06 1.113577e-05 9.396119e-06
[9931] 3.632872e-06 1.070051e-05 1.480068e-05 2.181409e-05 2.333744e-05
[9936] 2.453683e-05 1.581673e-05 1.883705e-05 4.360252e-05 4.190093e-05
[9941] 3.856703e-06 8.838088e-05 1.399614e-04 0.000000e+00 1.587114e-05
[9946] 0.000000e+00 1.487018e-05 0.000000e+00 0.000000e+00 2.088706e-06
[9951] 1.888650e-06 9.940963e-06 3.740264e-05 2.616738e-05 3.079246e-05
[9956] 9.182881e-06 0.000000e+00 0.000000e+00 0.000000e+00 7.518509e-06
[9961] 3.358298e-06 4.835253e-06 1.179798e-05 1.402502e-05 1.409108e-06
[9966] 7.696941e-06 9.003097e-06 1.034810e-05 1.528439e-05 0.000000e+00
[9971] 0.000000e+00 0.000000e+00 0.000000e+00 2.624682e-05 0.000000e+00
[9976] 1.099077e-05 9.506880e-06 0.000000e+00 1.137894e-05 1.433558e-05
[9981] 0.000000e+00 0.000000e+00 1.379068e-05 8.650746e-06 3.743000e-06
[9986] 0.000000e+00 8.364188e-05 0.000000e+00 0.000000e+00 0.000000e+00
[9991] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[9996] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10001] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10006] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10011] 0.000000e+00 0.000000e+00 0.000000e+00 5.229016e-08 7.599961e-06
[10016] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10021] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10026] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10031] 0.000000e+00 0.000000e+00 0.000000e+00 3.538543e-06 3.648946e-06
[10036] 1.193370e-05 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10041] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10046] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10051] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10056] 0.000000e+00 0.000000e+00 0.000000e+00 1.420944e-05 1.389582e-09
[10061] 3.683050e-05 2.085348e-05 0.000000e+00 0.000000e+00 1.640418e-05
[10066] 9.385660e-06 9.066886e-06 0.000000e+00 0.000000e+00 1.212919e-05
[10071] 6.153039e-06 8.204537e-06 1.251473e-05 2.117006e-05 2.343564e-05
[10076] 0.000000e+00 0.000000e+00 5.296602e-06 0.000000e+00 0.000000e+00
[10081] 5.668664e-06 0.000000e+00 0.000000e+00 1.087549e-05 5.311981e-06
[10086] 1.330456e-05 7.230244e-06 1.267972e-05 0.000000e+00 0.000000e+00
[10091] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10096] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.417702e-07
[10101] 1.169280e-06 3.891322e-06 2.280142e-06 0.000000e+00 6.744273e-06
[10106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
[10111] 0.000000e+00 8.722272e-06 0.000000e+00 9.256178e-06 8.144799e-06
[10116] 6.795240e-06 8.999001e-06 1.070536e-05 0.000000e+00 1.027576e-05
[10121] 1.576335e-05 0.000000e+00 0.000000e+00 0.000000e+00 1.360471e-05
[10126] 1.425764e-05 1.265967e-05 6.837101e-06 7.175901e-06 0.000000e+00
[10131] 0.000000e+00 6.115519e-06 0.000000e+00 4.280826e-06 3.517401e-06
[10136] 2.034884e-06 5.024481e-06 4.286403e-06 1.891131e-05 2.942515e-06
[10141] 0.000000e+00 2.204166e-05 0.000000e+00 0.000000e+00 2.858436e-06
[10146] 0.000000e+00 3.331110e-06 1.886007e-06 0.000000e+00 0.000000e+00
[10151] 3.767866e-06 3.437492e-06 1.948246e-06 9.555560e-06 3.517121e-05
[10156] 4.783468e-06 1.059869e-09 1.899528e-05 3.204048e-06 2.962181e-06
[10161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.411923e-06
[10166] 6.911184e-06 1.480042e-05 8.658562e-07Code
saveRDS(nkde_result_bangkok,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/nkde_result_bangkok.rds")Code
saveRDS(nkde_result_pathum_thani,"/Users/yuhu/Desktop/Geospatial Analytics and Applications/nkde_result_pathum_thani.rds")Code
saveRDS(nkde_result_Nakhon_Pathom, "/Users/yuhu/Desktop/Geospatial Analytics and Applications/nkde_result_Nakhon_Pathom.rds")Code
nkde_result_bangkok <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/nkde_result_bangkok.rds")
nkde_result_pathum_thani <- readRDS("/Users/yuhu/Desktop/Geospatial Analytics and Applications/nkde_result_pathum_thani.rds")This process applies the Network Kernel Density Estimation (NKDE) method to estimate the density of road accidents across different regions (Bangkok, Pathum Thani, Samut Prakan, and Nakhon Pathom). For each region, the road network is divided into “lixels” (linear pixels), and accidents are distributed along these lixels. The quartic kernel is used for smoothing the density with a bandwidth of 500 meters to capture the spatial distribution of accidents. The process standardizes the bandwidth (div = “bw”) and uses a simple method for the density calculation, applied on a 200x200 grid for each region. The function outputs detailed results (verbose = TRUE) for further analysis of accident hotspots along the road networks.
5.2 Visualising NKDE
5.2.1 Resampling kernel density
Code
sample_bangkok$density <- nkde_result_bangkok
lixels_bangkok$density <- nkde_result_bangkok
sample_bangkok$density <- sample_bangkok$density * 10000
lixels_bangkok$density <- lixels_bangkok$density * 10000Code
sample_pathum_thani$density <- nkde_result_pathum_thani
lixels_pathum_thani$density <- nkde_result_pathum_thani
sample_pathum_thani$density <- sample_pathum_thani$density * 10000
lixels_pathum_thani$density <- lixels_pathum_thani$density * 10000Code
samples_Nakhon_Pathom$density <- nkde_result_Nakhon_Pathom
lixels_Nakhon_Pathom$density <- nkde_result_Nakhon_Pathom
samples_Nakhon_Pathom$density <- samples_Nakhon_Pathom$density * 10000
lixels_Nakhon_Pathom$density <- lixels_Nakhon_Pathom$density * 10000The results from the Network Kernel Density Estimation (NKDE) to both the sample points and lixel segments for each region (Bangkok, Pathum Thani, Samut Prakan, and Nakhon Pathom). The NKDE results represent accident density estimates along the road networks. Afterward, the density values are rescaled from “events per meter” to “events per kilometer” by multiplying the densities by 10,000, ensuring that the density values are expressed in a more interpretable unit of analysis (events per kilometer). This allows for a clearer understanding of the spatial distribution of accident densities along the road network.
5.5.2 Visualising the NKDE Data
Code
tmap_mode('view')
tm_shape(lixels_bangkok) +
tm_lines(col = "density", palette = "YlOrRd", title.col = "Density", lwd = 2) +
tm_shape(acc_in_bangkok) +
tm_dots(size = 0.1, col = "blue", alpha = 0.5, title = "Accidents")Code
tmap_mode('plot')tmap mode set to plottingCode
tmap_mode('view')tmap mode set to interactive viewingCode
tm_shape(lixels_pathum_thani) +
tm_lines(col = "density", palette = "YlOrRd", title.col = "Density", lwd = 2) +
tm_shape(acc_in_pathum_thani) +
tm_dots(size = 0.1, col = "blue", alpha = 0.5, title = "Accidents")